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01 · CONTACT
Overview

GCU MOSTLY DETERMINISTIC / REGISTRY: FLORIDA / COMMISSIONED 2026 / STATUS: COMMISSIONING

Reliable systems from unreliable parts.

Mostly Deterministic designs and builds agentic AI platforms for enterprises. Architecture, engineering, evaluation, and the guardrails that let a probabilistic model do a dependable job.

> MIND:The same input will produce the same output. Probably.

02 · MISSION PROFILE
What we build

What we build

Six capabilities, one unit. Each is delivered as working software, not a slide.

  • CAP-01CONFIDENCE0.98

    Platform architecture

    The foundation an enterprise needs to build and run agents at scale: orchestration, retrieval, grounding, memory, and tool integration.

  • CAP-02CONFIDENCE0.97

    Agent engineering

    Agents and the components around them, built hands-on: multi-agent orchestration, RAG pipelines, function calling, and Model Context Protocol integrations.

  • CAP-03CONFIDENCE0.96

    Model and context engineering

    Choosing and routing between models, and engineering the prompts and context that decide how they behave.

  • CAP-04CONFIDENCE0.99

    Evaluation and observability

    Testing, evaluation, and monitoring that show whether an agent is doing its job, before launch and after.

  • CAP-05CONFIDENCE0.99

    Guardrails and governance

    Identity, access control, auditability, data governance, and responsible AI requirements built in from the first commit.

  • CAP-06CONFIDENCE0.94

    Enterprise integration

    Working with architecture, security, and platform teams so the system fits the organization it has to live in.

> MIND:Confidence figures are illustrative. That one is 1.00.

03 · OPERATING PRINCIPLES
How we work

Standing orders

  1. SO-01

    Measure before trusting

    An agent that hasn't been evaluated is a rumor. Evaluation is built alongside the feature.

  2. SO-02

    Constrain the blast radius

    Agents get the access they need and no more. Every action leaves a trail.

  3. SO-03

    Boring where it counts

    Novel models, conventional engineering. The interesting part should be the capability, never the outage.

  4. SO-04

    Leave it runnable

    The client's team should be able to operate, extend, and question everything after the unit departs.

SYSTEMS ABOARD / What we build on

  • Azure AI Foundry
  • Azure OpenAI
  • Azure AI Search
  • Microsoft Fabric
  • Claude
  • Gemini
04 · COMPLEMENT
Who

Complement: one

CREW 01 / FounderSTAKE 100%

Daniel Rolfe

Software architect

Designs and builds AI agent platforms for large organizations, from architecture through production code. Works at the intersection of software architecture and applied AI, with a focus on agentic infrastructure, LLM systems, and voice.

  • ARCHITECTURE
  • AGENTIC AI
  • LLM SYSTEMS
  • VOICE

SISTER SHIPAlso aboard the GSV Well, It Compiled, a separate vessel. See Vertrus.

> MIND:The org chart is a dot.

DESIGNATION / About the name

Why “Mostly”

Software is supposed to be deterministic. Language models are not. The work happens in the gap: engineering around a probabilistic core until the whole thing is dependable enough to run a business on.

Mostly.

A nod to the ship Minds of Iain M. Banks's Culture novels, who choose their own names.

05 · HAIL
Get in touch

Open a channel

Building an agent platform, or trying to make one behave? Send a signal. Replies come from the one human aboard.

© 2026 MOSTLY DETERMINISTIC LLC · FLORIDALAST BUILD: PASSED. MOSTLY.